Heterogeneous treatment effect bounds under sample selection with an application to the effects of social media on political polarization
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DOI: 10.1016/j.jeconom.2024.105856
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- Phillip Heiler, 2022. "Heterogeneous Treatment Effect Bounds under Sample Selection with an Application to the Effects of Social Media on Political Polarization," Papers 2209.04329, arXiv.org, revised Jul 2024.
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Cited by:
- Ying-Ying Lee & Chu-An Liu, 2024. "Lee Bounds with a Continuous Treatment in Sample Selection," Papers 2411.04312, arXiv.org, revised Feb 2025.
- Phillip Heiler & Michael C. Knaus, 2021.
"Effect or Treatment Heterogeneity? Policy Evaluation with Aggregated and Disaggregated Treatments,"
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- Heiler, Phillip & Knaus, Michael C., 2022. "Effect or Treatment Heterogeneity? Policy Evaluation with Aggregated and Disaggregated Treatments," IZA Discussion Papers 15580, Institute of Labor Economics (IZA).
- Phillip Heiler & Asbj{o}rn Kaufmann & Bezirgen Veliyev, 2024. "Treatment Evaluation at the Intensive and Extensive Margins," Papers 2412.11179, arXiv.org.
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More about this item
Keywords
Affective polarization; Debiased/double machine learning; Effect bounds; Facebook; Partial identification;All these keywords.
JEL classification:
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
- D72 - Microeconomics - - Analysis of Collective Decision-Making - - - Political Processes: Rent-seeking, Lobbying, Elections, Legislatures, and Voting Behavior
- L82 - Industrial Organization - - Industry Studies: Services - - - Entertainment; Media
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